Principal Software Developer – AI Data Architect

Caseware is one of Canada's original Fintech companies, having led the global audit and accounting software industry for over 30 years, with more than 500,000 users across 130 countries and available in 16 different languages. While you might not have heard of us (yet) over 36,000 accounting and audit professionals list Caseware as a skill on their LinkedIn profiles!

We are seeking a Principal Software Developer – AI Data Architect to drive the technical vision and architectural strategy of Caseware's AI-Ready Data Platform. This role will define the enterprise data architecture, patterns, and modeling standards that deliver trusted, governed, high-quality data products forming a foundational data platform for our cloud offerings, enabling AI capabilities and secure interoperability with customer systems, while powering analytics and strengthening our core products.

This role requires hands-on experience delivering data for AI workflows and practical familiarity with modern LLM tooling and AI platform integration patterns. You will apply this experience to build a data foundation that supports AI workflows and agentic capabilities, analytics, and customer interoperability.

This is a key leadership role where you will act as a hands-on architect while mentoring the development team, guiding the long-term technical vision, shaping enterprise data architecture standards across teams, and contributing to crucial AI and data platform projects.

Location: This is a fully remote position located in Colombia.

What you will do:

- Lead AI-Ready Data Platform architecture and delivery: Define and execute the technical strategy for a scalable AI-Ready data platform, including the patterns and capabilities needed to make data usable for AI use cases and interoperability.
- Establish data architecture patterns: Create and evolve reference architectures, modeling standards, guardrails, and best practices for our foundational data platform, including medallion and lakehouse architecture, ingestion, normalization, data quality, and AI interoperability.
- Oversee key platform projects: Contribute heavily to AI-Ready data platform initiatives and cross-product data architecture improvements, including data layer re-architecture for our SE product, schema modernization, and data model evolution.
- Mentor and lead: Guide teams in delivering projects, fostering a mentorship culture, and ensuring adherence to high standards in data engineering practices, data modeling, data quality, and platform architecture.
- Drive best practices: Collaborate with R&D groups to implement best practices for making data AI-Ready and securely interoperable, including data contracts, ingestion and normalization standards, and improving consistency and reuse across products.
- Partner on data governance and security: Work with Security and product teams to define data classification, retention, tenant isolation, and access controls for AI-Ready datasets and data products.
- Enable adoption through paved roads: Provide reference implementations and blueprints that make it easy for teams to produce data products and integrate with the AI-Ready platform.
- Architect for data observability: Define and implement standards for data quality, lineage and traceability, data dictionary controls, freshness monitoring, and alerting, so data products are reliable and audit-ready.

What you will bring:

• 10+ years of experience in software development and data engineering, with at least 5 years in a senior technical leadership role, preferably as a Principal Developer or Data Architect.
  - Demonstrated experience architecting and enabling data for AI workflows in production, such as embedding pipelines, vector-based retrieval, RAG data workflows, and real-time/event-driven data flows that support agentic systems and AI integrations.
  - Experience with AI platform integration and orchestration patterns, including agent workflow orchestration and LLM/agent observability and evaluation, partnering closely with data science and engineering teams to operationalize AI-Ready datasets and pipelines. Familiarity with LangGraph, Langfuse, MCP, AWS Bedrock, AWS AgentCore, and LaunchDarkly is preferred.
  - Experience enabling secure interoperability patterns with customer AI systems, including governed data access, tenant-aware controls, and safe integration patterns for customer-managed AI workflows.
  - Experience defining AI and data governance and platform adoption standards in large organizations, including controls for privacy, access, auditability, safe reuse, and operational guardrails for AI-Ready datasets and data products.
  - Experience designing modern data platforms on cloud-native infrastructure (AWS preferred), including lakehouse patterns, medallion architecture, ETL/ELT pipelines, distributed processing with Spark, Trino, and MapReduce, analytics and AI-Ready data at scale, with strong operational practices.
  - Hands-on experience with core data technologies and integration patterns: MongoDB, Amazon DocumentDB, MS SQL Server, DynamoDB, AWS ElastiCache for Redis or Valkey; event streaming and queueing using SNS/SQS. Postgres, pgvector, and Kafka or Pub/Sub are an asset.
  - Hands-on experience with AWS data platform services: S3, S3 Express, Athena, Glue Catalog, Lake Formation, OpenSearch Serverless, S3 Vector Storage, Iceberg, Lambda, Step Functions, EKS, ETL on EMR, and EMR Serverless.
  - Proven ability to architect and deliver scalable, reliable data systems and product data architectures, guiding teams in data models, storage and integration architectures, data contracts, data domain taxonomy, schema and event versioning, and resolving performance and scale bottlenecks.
  - Proficiency in data movement and performance architecture: Experience designing replication, event sourcing, and CDC/change tracking strategies, safe historical reprocessing patterns, and performance optimization through query analysis, indexing, and partitioning.
  - Strong technical leadership: Experience mentoring teams, setting engineering and architecture standards, and influencing technical direction across multiple teams.
  - Experience working with DevOps teams, CI/CD pipelines, infrastructure-as-code, and operational tooling to deliver scalable, resilient data platforms and pipelines.
  - Communication and collaboration skills to align cross-functional teams and engage with senior leadership on technical strategy, trade-offs, and decisions and strong English language communication and collaboration skills.

Key Success Factors:

1) Establish a solid technical strategy: Collaborate with data platform, product, and architecture leadership to define the AI-Ready Data Platform's technical direction, ensuring alignment with business growth, scalability, and interoperability objectives.
2) Deliver architecture patterns and standards: Define, prototype, and socialize key data architecture patterns and modeling standards backed by reference documentation and architecture decision records that teams can apply consistently.
3) Advance key platform initiatives: Contribute significantly to AI-Ready Data Platform initiatives and cross-product data architecture improvements, strengthening the foundation for AI capabilities, interoperability, scalability, and performance.
4) Mentor and guide teams: Cultivate high-performing development teams, driving adoption of best practices in data modeling, data quality, governance, and operational excellence.

Technologies you'll work with:

1) Core (current): AWS S3, S3 Express, DynamoDB, Athena, Glue Catalog, Lake Formation, OpenSearch Serverless, S3 Vector Storage, EMR/EMR Serverless, Spark, Trino, MapReduce, Iceberg, Lambda, Step Functions, EKS, SNS/SQS; MongoDB, Amazon DocumentDB, MS SQL Server, Redis/Valkey; Java (Spring), Python.
2) AI platform & agent tooling (preferred familiarity): AWS Bedrock (including models such as Anthropic Claude), AWS AgentCore (Runtime/Gateway/Memory/Identity), LangGraph, Langfuse, MCP, LaunchDarkly; embeddings, vector retrieval, and RAG workflows; AWS Knowledge Bases; AWS Textract.
3) Observability & operations: CloudWatch, New Relic, OpenTelemetry.
4) Emerging: Kafka or Pub/Sub, LLM proxy layer (e.g. LLMProxy), Aurora PostgreSQL, pgvector.

Perks & Benefits

• Contrato a termino Indefinido with all the legal benefits

- Prepaid Medicine

- Life insurance and funeral assistance

• Internet allowance
  - Home office stipend
  - Competitive compensation — above the market average
  - 100% remote work environment and an excellent work-life balance
  - Opportunity to work for a growing global SaaS leader company
  - A culture that promotes independence, innovation, trust, and accountability
  - Open space to be creative, innovative, and strategize for the future
  - Mentorship by a highly experienced professional
  - Budget for training, we want you to grow
  - 5 Personal Time Off days per year
  - Sick Leave Top up to total 100% of salary paid by the employer from Day 3 to 90.
  - Recognition Award, additional paid time off in recognition of the corresponding year of service
  - Upgrade vacation starting at 5 years of service

What's in it for you:

1) Innovation is at our core. We work with cutting-edge technology in accounting and financial reporting, constantly pushing the boundaries to create impactful software solutions.
2) We are committed to a collaborative culture, where your ideas are valued, and knowledge sharing is encouraged within a supportive, inclusive team.
3) Work-life balance is important to us. We offer flexible work options, remote opportunities, and generous time-off policies to ensure a healthy work-life balance.
4) We offer competitive compensation, including a competitive salary and comprehensive benefits such as health insurance and retirement plans.
5) We are driven by impactful work. Your contributions directly affect how our clients manage financial processes and drive their success.
6) Recognition and rewards matter to us. We celebrate hard work through recognition programs, performance bonuses, and opportunities for career growth.
7) We embrace global opportunities. Work on international projects and collaborate with a diverse, global team.

Originally posted on Himalayas